Architectures

Scalable Spatiotemporal Graph Neural Networks AAAI 2023 Scalable Theory-Driven Regularization of Scene Graph Generation Models AAAI 2023 Scalable Transformer for PDE Surrogate Modeling NeurIPS 2023 Scalable Video Object Segmentation with Simplified Framework ICCV 2023 Scale-Aware Modulation Meet Transformer ICCV 2023 Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting ICLR 2023 Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning ICCV 2023 Scale-Space Hypernetworks for Efficient Biomedical Image Analysis NeurIPS 2023 SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency ICLR 2023 Scaling Law for Document Neural Machine Translation EMNLP 2023 Scaling Laws for a Multi-Agent Reinforcement Learning Model ICLR 2023 Scaling Laws For Deep Learning Based Image Reconstruction ICLR 2023 Scaling Laws for Generative Mixed-Modal Language Models ICML 2023 Scaling Laws for Multilingual Neural Machine Translation ICML 2023 Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling? EMNLP 2023 Scaling MLPs: A Tale of Inductive Bias NeurIPS 2023 Scaling Spherical CNNs ICML 2023 Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks AAAI 2023 Scaling Up GANs for Text-to-Image Synthesis CVPR 2023 Scaling Vision-Language Models with Sparse Mixture of Experts EMNLP 2023 Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer NeurIPS 2023 ScanDMM: A Deep Markov Model of Scanpath Prediction for 360deg Images CVPR 2023 ScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform Discharges AAAI 2023 SCConv: Spatial and Channel Reconstruction Convolution for Feature Redundancy CVPR 2023 Scene as Occupancy ICCV 2023